In the oil and gas industry, modeling of the subsurface is typically utilized for visualization and to assist with analyzing the subsurface volume for potential locations for hydrocarbon resources. Accordingly, various methods exist for estimating the geophysical properties of the subsurface volume (e.g., information in the model domain) by analyzing the recorded measurements from receivers (e.g., information in the data domain) provided that these measured data travel from a source, then penetrate the subsurface volume represented by a subsurface model in model domain, and eventually arrive at the receivers. The measured data carries some information of the geophysical properties that may be utilized to generate the subsurface model.
The interpretation of seismic data often involves estimation of the local geometry in the measured information. Such information is useful for both interactive applications (e.g., in the form of a set of attributes) and/or in automated pattern recognition systems. The local geometry can be described by various techniques, such as estimating the tangents to peaks, estimating troughs or zero-crossings, computing the tangent planes to events. Alternatively, the local geometry may be interpreted as the local geometry of curves of equal value, such as iso-curves and/or iso-surfaces. Regardless, the local dips and azimuths (e.g., geometry) are frequently used seismic attributes. Accordingly, several methods exist to determine and utilize this information.
As a first example, one or more correlation-based methods may be utilized. See, e.g. as described in Neidell and Taner, “Semblance and other coherency measures for multichannel data”, Geophysics 36, 482-497 (1971). The document describes that the calculation of vectors should be considered local measurements. However, the methods described in the paper do not appear to apply to global volume flattening.
Yet another method is referred to as instantaneous phase method. See, e.g., U.S. Pat. No. 5,724,309. This method describes utilizing instantaneous phase and the derivatives of instantaneous phase as display and/or plot attributes for seismic reflection data processing and interpretation for two-dimensional and three-dimensional seismic data. However, this method does not appear to enhance the dip vector.
Also, in the Fomel reference, it describes how to obtain local dips from a global optimization calculation. See, e.g., Fomel, S., “Applications of plane-wave destruction filters”, Geophysics 67, 1946-1960 (2002). This reference predicts a new trace from an existing trace and the optimization minimizes the total error over all such predictions. Despite the reduction in errors, areas of poor data quality (e.g., the measurement data is poor quality) may skew predictions and therefore affect the total quality of the dip estimates. This described method is not easily adapted to ignore such areas of poor data quality.
Other techniques include various flattening methods to assist interpretation. Examples of flattening methods include Seismic Horizon Skeletonization in Intl. Patent Application Pub. No. 2009/142872) or techniques in U.S. Pat. No. 7,769,546 to Lomask et al. and a paper entitled “Flattening without picking”, Geophysics 71, 13-20 (2006). However, these techniques are not utilized to enhance dip estimates.
As the recovery of natural resources, such as hydrocarbons, rely, in part, on subsurface models, a need exists to enhance subsurface models of one or more geophysical properties. In particular, a need exists to enhance dip estimates to improve volume flattening. Further, a need exists for a dip refinement approach that may utilize the whole data set or may be utilized on a portion of the data set.